The practice of medicine has greatly advanced as evidenced by patients being treated with previously incurable diseases, such as cancer. One reason, among many, for the advancement of medicine is a result of improvement of medical imaging technology. Medical images may include many different types of images of the human body, including radiological images, CAT scan images, endoscopic images, magnetic resonance images, etc. Through the use of medical imaging technology, medical professionals are able to see images of internal organs, for example, of patients to help diagnose medical conditions of the patients. Medical imaging allows for diseases, such as breast cancer, to be diagnosed in early stages, which greatly improves chances of recovery. While medical imaging technology has significantly improved medical care, because of the nature of creating and interpreting medical images, radiological or other imaging techniques, inaccuracies in the imaging and interpretation processes of the medical images may result. Because of the inaccuracies in the imaging and interpretation processes, patient medical conditions are often misdiagnosed.
Misdiagnosis of a medical condition, such as a disease, may come in the form of false positives, false negatives, and equivocal diagnoses. A false positive is a detection of a disease that does not exist. A false negative is a failure to detect a disease that is present in a patient. An equivocal diagnosis is a statement that a definitive diagnosis cannot be made based on the information available (e.g., “cancer cannot be ruled out”). Each of these misdiagnoses results in higher costs of treatment, additional suffering to patients, and additional burden on the healthcare system as a whole. It has been estimated by the American College of Radiology that frequency of misdiagnosis of radiological imaging interpretations is as high as 30%. And, given that it has been estimated that 40% to 60% of total healthcare spend is influenced by radiological imaging and interpretations therefrom, misdiagnoses results from misinterpretation of medical imaging has a large impact on the healthcare system.
An example of the effects of a misdiagnosis is as follows. A medical image reading professional identifies a spot on a lung. The lung spot may be any of a number of different medical conditions, including a benign solitary pulmonary nodule, small cell lung carcinoma, non-small cell lung carcinoma, or any number of other medical conditions. If the medical image reading professional determines that the lung spot is a benign solitary pulmonary nodule, but also denotes that “cancer cannot be ruled out,” a treating medical professional is compelled to perform additional testing, a biopsy of the lung spot, and possibly surgery to remove the lung spot, to avoid a malpractice claim. The cost for each of these additional diagnostic treatments can be very high from financial, patient anxiety and pain, and medical system resource perspectives. If it turns out that after the additional diagnostic treatments that the patient had a benign, solitary pulmonary nodule that could have been identified by the medical image reading professional at the initial medial image reading, all of the additional diagnostic treatments would have been avoided.
Although medical professionals are considered to be highly regarded, and justifiably so in most cases, medical professionals are not all trained in the same manner or have the same level of proficiency as one another. As in all professions, some medical professionals may have better education, training, or any other differentiator than other medical professionals. For example, one medical image reading professional may have better eyesight or cognitive reasoning skills than another and, therefore, be better at determining a correct or more accurate diagnosis than another with worse eyesight or cognitive reasoning skills. One problem that is a dilemma for the healthcare system is that absent clear cases of malpractice that result in the unfortunate injury or death of a patient, it is difficult to quantitatively determine proficiency of medical professionals given the vast number of medical professionals in the healthcare system.